Audio examples for the paper:

Martínez Ramírez M. A., Benetos, E. and Reiss J. D., “Modeling plate and spring reverberation using a DSP-informed deep neural network” in the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020.

View the source code.

Download the dataset.

plate

- input

- target

- model-1

- model-2

 

spring

- input

- target

- model-1

- model-2

 

Model

Block diagram of the proposed model; adaptive front-end, latent-space and synthesis back-end:

Detailed architecture of adaptive front-end:

Input frame size of 4096 samples and ±4 context frames.

Block diagram of the latent-space:

Detailed architecture of the latent-space:

Block diagram of the synthesis back-end:

Detailed architecture of the synthesis back-end:

Output frame size of 4096 samples.

Plate and Spring settings:

 

Citation

@inproceedings{martinez2020modeling,
title={Modeling plate and spring reverberation using a {DSP}-informed deep neural network},
author={Mart'{i}nez Ram'{i}rez, Marco A and Benetos, Emmanouil and Reiss, Joshua D},
booktitle={IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
month = {May},
year = {2020},
location = {Barcelona, Spain}
}